An intuitive, yet precise introduction to probability theory, stochastic processes, and probabilistic models used in science, engineering, economics, and related fields. The 2nd edition is a substantial revision of the 1st edition, involving a reorganization of old material and the addition of new material. The length of the book has increased by about 25 percent. The main new feature of the 2nd edition is thorough introduction to Bayesian and classical statistics. The book is the currently used textbook for "Probabilistic Systems Analysis," an introductory probability course at the MIT.

Practical tips for solving probability problems. Increase your chances of acing that probability exam or winning at the casino! Whether you are hitting the books or hitting the tables, working out probabilities can be a challenge. This book helps even the odds. The book covers set theory, counting, permutations and combinations, random variables, conditional probability, joint distributions, conditional expectations, gambling, and actuarial applications and probability modeling. And it is packed with real-life examples and straightforward, friendly explanations. > Buy Now

A Bayesian approach to science. This introduction to probability was written by a scientist for scientists. The author shows how Bayesian theory can be applied to inference from incomplete information. The book is a pleasure to read, especially the author's entertaining arguments against conventional theory. That is not to say that it is an easy read; on the contrary, the math is high-level and the problems are challenging. To follow the author's presentation, the reader will need to be familiar with applied mathematics at an advanced undergraduate level. > Buy Now

Excellent basic text covers set theory, probability theory for finite sample spaces, binomial theorem, probability distributions, means, standard deviations, probability function of binomial distribution, and other key concepts and methods essential to a thorough understanding of probability. Designed for use by math or statistics departments offering a first course in probability. 360 illustrative problems with answers for half. Only high school algebra needed. > Buy Now

This textbook is an introduction to probability theory using measure theory. It is designed for graduate students in a variety of fields (mathematics, statistics, economics, management, finance, computer science, and engineering) who require a working knowledge of probability theory that is mathematically precise, but without excessive technicalities. The text provides complete proofs of all the essential introductory results. Nevertheless, the treatment is focused and accessible, with the measure theory and mathematical details presented in terms of intuitive probabilistic concepts, rather than as separate, imposing subjects. > Buy Now

Geared toward advanced undergraduates and graduate students, this introductory text surveys random variables, conditional probability and expectation, characteristic functions, infinite sequences of random variables, Markov chains, and an introduction to statistics. Complete solutions to some of the problems appear at the end of the book; specifically, 43 pages of solutions. > Buy Now

Probability theory and models. This is an introductory probability text for college students. The book covers the fundamentals of probability theory (probabilistic models, discrete and continuous random variables, multiple random variables, and limit theorems). It also covers a number of more advanced topics - transforms, sums of random variables, least squares estimation, the bivariate normal distribution, and a fairly detailed introduction to Bernoulli, Poisson, and Markov processes. > Buy Now

Pages and pages of solved probability problems. Designed for students in various disciplines of engineering, science, mathematics, management, and business, this effective study tool includes hundreds of problems with step-by-step solutions and another 150 problems with hints or delayed answers. The solved problems illustrate and strongly reinforce vital theory and techniques. Topics taught include functions of random variables, expectation and limit theorems, estimation theory, decision theory, and queuing theory. > Buy Now

A fresh approach to probability. A pleasant surprise; a book that makes probability theory easy to understand. The author uses colorful examples (gambling, lotteries, etc.) and historical references (Newton, Einstein, etc.) to illustrate basic principles and stimulate reader interest. This book very clearly explains why probability works and how to apply it. > Buy Now